|
|
Absolute deviation, 绝对离差1 X2 J: L1 K5 o8 Q
Absolute number, 绝对数
/ T V1 ~8 O( \( y5 P1 ^5 d ZAbsolute residuals, 绝对残差
' S. T" K, k7 m- h0 K! x0 uAcceleration array, 加速度立体阵
E4 B' ` D$ G) {: zAcceleration in an arbitrary direction, 任意方向上的加速度# `9 @0 ^5 W" `0 }) h
Acceleration normal, 法向加速度
/ c; O$ V- u% RAcceleration space dimension, 加速度空间的维数
! {" i: Z; u1 }, P! F. ~; ?( |Acceleration tangential, 切向加速度
2 a& T+ o+ n/ r7 s. B9 V9 _! G) i4 ]Acceleration vector, 加速度向量* K7 y7 o; }8 G
Acceptable hypothesis, 可接受假设
7 l- @- S5 n2 Y8 o! K" J8 m& c. uAccumulation, 累积
1 ]: c2 n/ [% w2 L' o8 c, CAccuracy, 准确度
$ V- _, b0 }8 V" s& dActual frequency, 实际频数
( N3 d! E/ C' IAdaptive estimator, 自适应估计量
0 B% H$ e' H! XAddition, 相加) `: d! X( B8 b/ N9 E o0 Q# j
Addition theorem, 加法定理
) L& L- [: J3 C; X3 I; t. b$ E MAdditivity, 可加性- }/ C& ~: L$ R' _/ ]+ o3 J1 g
Adjusted rate, 调整率
0 e- a* r% X1 f) D2 N( jAdjusted value, 校正值) D, C/ a" q2 |: O/ z0 `
Admissible error, 容许误差3 F F' u. [8 ]. @
Aggregation, 聚集性
! Z0 w! o1 o" P! X" a& H, AAlternative hypothesis, 备择假设
& J# p0 K3 h3 K0 N/ q9 ]Among groups, 组间" i: f ]" }4 u; e7 i( S
Amounts, 总量
3 r- F* K/ r* d7 [) eAnalysis of correlation, 相关分析
" Z* h! H( G+ R7 |5 VAnalysis of covariance, 协方差分析/ F& N3 v) X6 C; |# s2 Y
Analysis of regression, 回归分析6 y- K: y! q/ {$ h Z- F- D! V
Analysis of time series, 时间序列分析6 K d* ^* g. T+ |6 H3 R U
Analysis of variance, 方差分析
. K( E: C" \) _ t. [7 _7 o& CAngular transformation, 角转换 A! P8 S7 Y9 ^6 d* t: s6 w* G
ANOVA （analysis of variance）, 方差分析: ] J4 K" M! a- m" a# b1 \
ANOVA Models, 方差分析模型
/ {6 m$ D) h/ E/ I/ FArcing, 弧/弧旋
* b0 f) ~, P! L' e' G7 TArcsine transformation, 反正弦变换
( [$ N+ {4 l2 H7 ]Area under the curve, 曲线面积
4 }" a% y* ?6 R$ b" E! ]+ sAREG , 评估从一个时间点到下一个时间点回归相关时的误差 , e/ A! p) {/ ^: q
ARIMA, 季节和非季节性单变量模型的极大似然估计
7 c% Q. E( ]0 R( q; s* X8 aArithmetic grid paper, 算术格纸
( K! h, ` E" P9 H* ]& V; g* tArithmetic mean, 算术平均数
* Y3 Q0 f6 M0 o0 v6 V, \) o3 RArrhenius relation, 艾恩尼斯关系, C) c% y; ^ Y" j
Assessing fit, 拟合的评估4 l3 y: ]: o% X* X
Associative laws, 结合律. f% F# E) a5 [7 `, d" k
Asymmetric distribution, 非对称分布
5 P5 q' V5 r' fAsymptotic bias, 渐近偏倚6 u) S) E5 w+ c6 q, j& Q1 W8 _" r
Asymptotic efficiency, 渐近效率
5 x5 t# }# G0 ~Asymptotic variance, 渐近方差) S/ ]2 \) d6 B: [
Attributable risk, 归因危险度
j3 V, W" ]# d7 g. EAttribute data, 属性资料
/ u' X/ ], ^0 v: |0 B2 Q+ NAttribution, 属性
9 K8 E# a: k t4 N( AAutocorrelation, 自相关
- J9 f9 J: {+ \- L) JAutocorrelation of residuals, 残差的自相关
% O: p1 m4 c2 ~+ a8 [Average, 平均数
; a; \3 H& j* ?) ? J0 FAverage confidence interval length, 平均置信区间长度) y7 N+ _- P, x6 [" G
Average growth rate, 平均增长率( V: D/ F9 B" o- m$ u8 O* j1 O* T0 P
Bar chart, 条形图
1 o3 H5 ^' B- G9 R. B$ bBar graph, 条形图7 b7 n2 e" x" |, A5 A
Base period, 基期, s8 ~- {2 W" B0 d: I
Bayes' theorem , Bayes定理
# n- E+ M# e h5 k4 t6 K' kBell-shaped curve, 钟形曲线
( |" y- o# }& nBernoulli distribution, 伯努力分布' K8 f) a4 L7 M+ H( U6 u* x1 S
Best-trim estimator, 最好切尾估计量! P3 t, n. y) [2 S, x! \* @
Bias, 偏性
9 D0 M) Z! @* q/ _3 q- N# Y2 oBinary logistic regression, 二元逻辑斯蒂回归
% u" t! R7 ~. P0 c% u9 H0 a3 `& zBinomial distribution, 二项分布
+ n2 h2 w C' w! x5 IBisquare, 双平方3 m/ |. V9 u+ ]$ n, M* H! Q
Bivariate Correlate, 二变量相关
1 o, Q; C# I0 W- b& W2 IBivariate normal distribution, 双变量正态分布+ b4 Q* F* q0 e
Bivariate normal population, 双变量正态总体: N7 Q. i# [* K/ v9 |5 F, O
Biweight interval, 双权区间& [# Y+ m; C9 F# D# H/ G, W
Biweight M-estimator, 双权M估计量0 z% b, o; D1 g3 q7 H4 S
Block, 区组/配伍组4 V& \) _' C! b9 z3 k% j1 [3 i$ ?
BMDP(Biomedical computer programs), BMDP统计软件包
1 @, t! }; W# M% Q/ r3 jBoxplots, 箱线图/箱尾图- a8 T" t( H0 C$ M5 f6 Y
Breakdown bound, 崩溃界/崩溃点8 Q1 a/ }' e p6 M5 d1 ~% z
Canonical correlation, 典型相关& u0 T: {; e3 X8 _6 }, s
Caption, 纵标目! r2 O: N3 Z' r2 Y" `! q( ]/ {* }) D
Case-control study, 病例对照研究
/ f7 W2 m3 x, S8 R. _) f- h5 E: gCategorical variable, 分类变量" N2 D2 Z2 w: d3 S+ V; Y
Catenary, 悬链线5 E" ?) p/ G5 S2 z
Cauchy distribution, 柯西分布% `7 d0 i. Y1 ^3 N0 f0 h
Cause-and-effect relationship, 因果关系) g0 w$ l5 F3 b% o% F8 W3 i' x+ J# \
Cell, 单元' z1 p# s( |3 B) U( G$ z* y
Censoring, 终检
: \1 y3 x; n( a+ h% [6 o( T" VCenter of symmetry, 对称中心, q2 e/ S& l4 D
Centering and scaling, 中心化和定标
: m, `9 o B1 c& ICentral tendency, 集中趋势
' K7 U8 I ~8 {# c W; k' CCentral value, 中心值" S2 O$ f3 y7 a" }8 O
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
8 L( m# K" L) m3 Z8 c% ^/ w- JChance, 机遇 {" [8 }# N5 D
Chance error, 随机误差
: k7 q( x/ s/ {$ S; l0 mChance variable, 随机变量% G: V( p/ I5 x3 `8 m( x* H- m
Characteristic equation, 特征方程+ u) v, z$ [4 l3 r" e
Characteristic root, 特征根
5 A- R% I# t8 j& d( QCharacteristic vector, 特征向量
0 v- y% a5 W5 u0 W! tChebshev criterion of fit, 拟合的切比雪夫准则
. {0 M' G& x" ^* ?Chernoff faces, 切尔诺夫脸谱图
. S3 U+ p- {- s3 i5 K. qChi-square test, 卡方检验/χ2检验: }# D: v ~) c
Choleskey decomposition, 乔洛斯基分解) Q5 M1 `" o) ^0 i+ d
Circle chart, 圆图
1 s& \8 U* r$ P3 L8 A9 A3 |5 r4 oClass interval, 组距9 ?, I7 l4 c# l: z! Q* w
Class mid-value, 组中值( A6 e+ f7 \. ?- }9 F
Class upper limit, 组上限4 O- d' h0 N2 q8 l5 C* f8 P
Classified variable, 分类变量8 H6 R1 k& b3 j Z
Cluster analysis, 聚类分析0 V- _* k7 s3 a1 K0 {2 I4 u3 \
Cluster sampling, 整群抽样6 o" g+ q" c* b, I* Q2 i! t# d
Code, 代码4 w/ s6 N" {5 O! B. M5 q* i
Coded data, 编码数据; G0 z+ B/ b8 K4 {7 `# y$ M
Coding, 编码- `) N* a% m) O& z% r
Coefficient of contingency, 列联系数9 @0 K' _, U" l- u
Coefficient of determination, 决定系数1 D( L) r- w( D6 k$ \! j
Coefficient of multiple correlation, 多重相关系数& K2 Y, G3 B$ X6 {! m' z1 y, n
Coefficient of partial correlation, 偏相关系数1 J; K3 _* \% h7 y/ t+ k1 O
Coefficient of production-moment correlation, 积差相关系数$ d8 u3 a' T0 k' |# a: d p% ]
Coefficient of rank correlation, 等级相关系数8 y7 L9 \9 Y8 R4 A5 S
Coefficient of regression, 回归系数
8 F: n1 ?1 a& d+ O( z; w% r7 `4 yCoefficient of skewness, 偏度系数
/ J$ c0 k" z( c9 D6 |' c0 I# ZCoefficient of variation, 变异系数 }/ O% |; Y3 _! K) I( {
Cohort study, 队列研究, Y$ g1 |( L, D5 F& P& B
Column, 列( A. \2 x* B* D
Column effect, 列效应; J* \2 x4 V7 d0 w
Column factor, 列因素2 B, u% ~6 p, [0 @3 M
Combination pool, 合并( Z5 [3 U8 [; Q7 D# e/ V
Combinative table, 组合表) S6 L( b2 j; }+ e. V4 ]- K
Common factor, 共性因子! b! B8 j/ Z2 l" {, {( W$ k
Common regression coefficient, 公共回归系数
$ x1 G- z9 `- w+ v( GCommon value, 共同值1 r T7 Z7 I2 s* c/ P7 ]
Common variance, 公共方差 w# n2 P8 w* Y
Common variation, 公共变异8 w8 B3 U& L+ x" k# P: G, U$ e
Communality variance, 共性方差
" ~% x, O. R* n) Y$ ]Comparability, 可比性
" u& `9 y+ v3 B8 ~Comparison of bathes, 批比较
4 u+ I. g9 o) N+ n* l' f7 DComparison value, 比较值
, b5 h. c+ ~0 Y( Z/ i. i. FCompartment model, 分部模型
, o+ U5 [: |7 H. _, |3 NCompassion, 伸缩5 }* G" H7 ^- _
Complement of an event, 补事件
' Q+ S7 y+ ]: Z3 M2 m( MComplete association, 完全正相关! l, A; w/ S- Q, t
Complete dissociation, 完全不相关6 X/ V# N. N5 H
Complete statistics, 完备统计量% D$ ~: @( }2 }7 @/ q+ j
Completely randomized design, 完全随机化设计( p2 ~$ P) N. `& u4 F+ V5 X
Composite event, 联合事件* E6 z5 L j8 }! z% l7 G0 i
Composite events, 复合事件( t- d' i- W: i/ r2 w1 s7 G& o) ^
Concavity, 凹性
, d$ ?9 B* I3 T. `0 i- rConditional expectation, 条件期望5 ~% ~2 B& ^) L u
Conditional likelihood, 条件似然9 {& Y' r( R N
Conditional probability, 条件概率8 L* ]- z0 H7 P: H9 h0 q# s# ]
Conditionally linear, 依条件线性3 U* F& h0 L* P3 E* K1 ^
Confidence interval, 置信区间
& e# p0 ~" u# d- ?3 n# {) QConfidence limit, 置信限 [! M. C0 W; t' a/ N# `
Confidence lower limit, 置信下限
. ?# f+ `7 T: h! F' NConfidence upper limit, 置信上限
. H- \0 _9 \, W5 Z) e2 DConfirmatory Factor Analysis , 验证性因子分析! b. G* M+ y: p6 @ H9 V
Confirmatory research, 证实性实验研究1 `$ S0 P! f7 X2 ^' e
Confounding factor, 混杂因素, p: h6 D) \) h" d( o* M
Conjoint, 联合分析, v6 x/ W( Q v9 T4 S; G, s; _
Consistency, 相合性
0 T7 x+ h9 M2 W: ]6 R6 ?2 ZConsistency check, 一致性检验3 Q" n3 [9 k( m/ k! u# m. ?
Consistent asymptotically normal estimate, 相合渐近正态估计
. c7 t& r) D8 p5 q& HConsistent estimate, 相合估计3 [& G. a0 y0 A9 ?# B* ?
Constrained nonlinear regression, 受约束非线性回归. p: [1 k( }9 t) t" G
Constraint, 约束
. o! M h* F! N9 g2 t" A& E. R- }Contaminated distribution, 污染分布
q4 N* E; j1 m% `Contaminated Gausssian, 污染高斯分布
( ]1 a& ^' p- H% S7 OContaminated normal distribution, 污染正态分布: s( X) Q& s3 } j8 Y' B2 }
Contamination, 污染; d/ m6 M0 ] A4 y) @1 C7 N# T
Contamination model, 污染模型. y/ J. t7 z0 Y" s. B! V& Y
Contingency table, 列联表
1 A* s Z' p7 z5 L N7 x! ~7 m9 eContour, 边界线7 u0 c- j8 l& B, @$ T( N
Contribution rate, 贡献率
) v. J9 D$ m5 g' q8 h( U# C6 BControl, 对照5 z9 ?4 x2 k& k! J- y1 `2 m [
Controlled experiments, 对照实验
r9 {+ b' \9 dConventional depth, 常规深度" t: m+ v, |8 M# X5 H t
Convolution, 卷积
9 y4 U' K3 U7 oCorrected factor, 校正因子
: [( X# B; W/ ~6 k4 A ^; lCorrected mean, 校正均值
7 Q5 ~1 n/ R, j/ ?Correction coefficient, 校正系数
0 H$ V( ~8 v& N5 ^' u& l5 s3 W+ TCorrectness, 正确性
. Y5 |9 o& \/ J8 F2 G1 PCorrelation coefficient, 相关系数9 m) j" H% q j3 c4 C8 b7 \5 p
Correlation index, 相关指数3 C2 o' N Y1 Z) v. \
Correspondence, 对应' p) N, `) ]2 A/ X$ v }: N
Counting, 计数
: o8 o2 t/ u: J% A5 P& [Counts, 计数/频数
9 d4 c6 V: u6 c& Z4 T; i) H, R* g2 pCovariance, 协方差/ R5 f1 `7 h; c+ i# b
Covariant, 共变 ) ^+ I/ R" p7 i
Cox Regression, Cox回归 L8 R/ _/ U B V) y
Criteria for fitting, 拟合准则
. F/ K1 f; A, f' e, J1 H2 _8 ECriteria of least squares, 最小二乘准则- m$ P- P; e! n
Critical ratio, 临界比! C' s5 W) `. e) j
Critical region, 拒绝域% j8 u! m3 ^2 `- q
Critical value, 临界值
/ C. u/ d* ?: s+ G; o' Q' [Cross-over design, 交叉设计 `% x& w) g1 B/ E& w# e
Cross-section analysis, 横断面分析1 h; s2 ?* u) W
Cross-section survey, 横断面调查: {) O2 H* B9 C$ u! P) s
Crosstabs , 交叉表
D. [) u& N i5 ?0 Q6 _9 oCross-tabulation table, 复合表+ B; e" r7 m: X; m: x
Cube root, 立方根
% \ d! M# U2 Z) Y/ ?! SCumulative distribution function, 分布函数0 [% I. R+ F( N% F
Cumulative probability, 累计概率
1 \0 q3 o) w0 H; WCurvature, 曲率/弯曲
( A k8 f4 j5 m FCurvature, 曲率( @+ k4 }$ H5 n. D5 {
Curve fit , 曲线拟和 - z, b& d1 K( H9 ]: {
Curve fitting, 曲线拟合
, U( b* L* K; }! m: f% F6 yCurvilinear regression, 曲线回归- z1 R7 `# H' y% ~0 O$ ~# a
Curvilinear relation, 曲线关系" J/ {6 j) K- ?" m2 @4 P. U, k( c* [" r
Cut-and-try method, 尝试法
* x4 a7 Y' a8 G" l \+ D: N1 t* NCycle, 周期% G5 Z: v j8 q G6 D# b* ^
Cyclist, 周期性
4 ^! r2 R$ ~/ Y" a$ cD test, D检验
8 |7 o3 L; L$ Y: t+ @% {Data acquisition, 资料收集1 k4 f' g9 b5 U! u2 \
Data bank, 数据库1 ]- g0 ^( {. o# C& q; \
Data capacity, 数据容量
5 g1 S/ y. j, Z" N/ g9 v; \$ SData deficiencies, 数据缺乏( [1 K+ u0 p2 G& D. E
Data handling, 数据处理- }- r+ a. V3 d& }
Data manipulation, 数据处理1 m5 w% B5 B' ^; d1 a4 y6 O
Data processing, 数据处理
0 [' @9 J+ K: l) ?) fData reduction, 数据缩减
0 N, F+ l. z4 w" ~- J, t& l# RData set, 数据集4 y' ~) ?1 h, t/ H
Data sources, 数据来源
+ P5 {& M$ c& C+ @4 [% q. |# `Data transformation, 数据变换
d% p4 R$ {/ Z" y3 _9 fData validity, 数据有效性
, w5 S' R2 @3 aData-in, 数据输入" G: a5 i8 J- g4 G8 y
Data-out, 数据输出# ^+ k6 \: m6 S0 `- m
Dead time, 停滞期) K7 E0 w) g1 [' s6 ~' {
Degree of freedom, 自由度0 i1 S& o1 Z# ^$ g
Degree of precision, 精密度
- I- t2 G! w A, v2 p* v( c3 r4 r WDegree of reliability, 可靠性程度# v2 U7 h' b! v
Degression, 递减6 j. D, k- f2 M1 g
Density function, 密度函数% B' M; g6 N1 m; ?2 V8 d$ u
Density of data points, 数据点的密度6 w+ @; s- h& K
Dependent variable, 应变量/依变量/因变量4 D. k0 h5 u) t1 }% ]) h6 i
Dependent variable, 因变量) E. e% J. }5 [9 e/ T
Depth, 深度
. X0 l: w, H9 G$ S' Y dDerivative matrix, 导数矩阵7 u. j3 C7 d, d( F$ B C' O
Derivative-free methods, 无导数方法
& \) Y8 G8 ?' {* B; _: bDesign, 设计# ~7 p l7 |8 P' i* W E" A% J
Determinacy, 确定性$ Z- q, b, K: g; s- A
Determinant, 行列式
/ W( z3 B; y" ^# k/ K8 mDeterminant, 决定因素' I( U- U, U* Y U7 k6 v' ?
Deviation, 离差: Z9 K( c1 G( A: \2 p/ p
Deviation from average, 离均差' v. _# L8 A5 }4 R# j% B
Diagnostic plot, 诊断图
+ U5 a/ R$ }6 uDichotomous variable, 二分变量* O9 M; \0 M- X* n9 H7 w$ G
Differential equation, 微分方程 H) q. p& S2 d" i( K
Direct standardization, 直接标准化法& d. Y) h: }' W0 \' g. ^& ]( \ b
Discrete variable, 离散型变量
' ]( S1 o9 h0 P8 p. KDISCRIMINANT, 判断
9 A( _, b! \! F0 p2 ZDiscriminant analysis, 判别分析6 |2 }4 |& L8 I0 s+ K/ O+ z8 T
Discriminant coefficient, 判别系数/ g1 \4 y) y9 S' [' t
Discriminant function, 判别值
* O' C. W* X$ s- F. I" ~9 tDispersion, 散布/分散度: s) C; Q7 D$ n. J
Disproportional, 不成比例的
/ i' ]* a" P5 z4 g& wDisproportionate sub-class numbers, 不成比例次级组含量! q, ]$ z# a' f- {* l$ _
Distribution free, 分布无关性/免分布6 X1 W2 S; h4 F: M: [8 v% H" U% [: p# _* f
Distribution shape, 分布形状
5 f+ J& x" M* q n$ P% VDistribution-free method, 任意分布法/ I8 ]# [8 U- G4 P
Distributive laws, 分配律
& r% P" B; P% @" K+ I9 f, q6 kDisturbance, 随机扰动项
5 a a. s! D# O1 S9 I$ J dDose response curve, 剂量反应曲线4 e3 }( h: N' T) L7 d k, D" v
Double blind method, 双盲法8 F5 p+ v6 ` T0 i& L
Double blind trial, 双盲试验
2 e6 w& M: @9 X2 j BDouble exponential distribution, 双指数分布( c' @ Q: i9 f" K
Double logarithmic, 双对数6 Q0 o' u8 B' F
Downward rank, 降秩
& ]" Z* I: T. U3 y# e) m% {Dual-space plot, 对偶空间图' _, d m3 R; M" }- U: u# V
DUD, 无导数方法
6 u. c8 Y4 W; CDuncan's new multiple range method, 新复极差法/Duncan新法
5 A' _" `$ D# w- dEffect, 实验效应
) ]' @' C: R/ ^0 GEigenvalue, 特征值$ C x+ b+ g+ z1 s% O
Eigenvector, 特征向量
$ _0 y3 Z# M& h+ O( g, GEllipse, 椭圆7 m/ U0 Y8 H* B' p. |& y# ] x
Empirical distribution, 经验分布" L$ w' x0 k8 B5 o2 X( {# u
Empirical probability, 经验概率单位
4 K9 f8 a% V& j" X& G+ dEnumeration data, 计数资料
# R* F2 f# [$ {8 s4 J/ TEqual sun-class number, 相等次级组含量
1 y6 a% q2 o+ {" j9 P% p( |& u+ `' ]Equally likely, 等可能2 L8 m. v; ]. V, Y
Equivariance, 同变性! R3 E! h! [0 _ |3 y O3 h
Error, 误差/错误/ c/ z7 M5 L8 u) h$ ~ e+ J
Error of estimate, 估计误差. _+ E' k# Q v# O6 `
Error type I, 第一类错误, V4 _ y# z: T7 }
Error type II, 第二类错误
5 N6 A! \8 }+ ?1 @6 OEstimand, 被估量' c7 A1 A; y7 x8 L9 q4 ^: n8 S
Estimated error mean squares, 估计误差均方6 @ _& Z- t, L2 i! ^
Estimated error sum of squares, 估计误差平方和 z9 }/ t( d. Z
Euclidean distance, 欧式距离% i, _6 K2 i4 F8 ~+ p% G( Q
Event, 事件
" J4 C1 ^/ [- REvent, 事件
& ]! U8 c2 T3 jExceptional data point, 异常数据点
6 q+ M$ D+ t% l; p2 zExpectation plane, 期望平面
* T; l2 m8 e" i- h, o% XExpectation surface, 期望曲面
% y- n- }' b0 H `8 fExpected values, 期望值 G6 @( U9 ]: Z
Experiment, 实验
& O" ?& p4 B# P4 v$ [6 E' PExperimental sampling, 试验抽样. M7 h2 z8 k. L
Experimental unit, 试验单位% f1 T+ N0 b% S; i
Explanatory variable, 说明变量5 z1 a& }" S; S" Y2 O
Exploratory data analysis, 探索性数据分析
( c9 M) [' {2 a4 {8 bExplore Summarize, 探索-摘要
! L# J2 M" u3 Q! y, r, tExponential curve, 指数曲线" P6 W% o& u1 ^- r2 j2 E
Exponential growth, 指数式增长" l5 _/ T# Q5 T w d
EXSMOOTH, 指数平滑方法 & [% l0 h6 s* a" b/ c
Extended fit, 扩充拟合. U' _0 W# H2 u5 o
Extra parameter, 附加参数& F% D9 h* R) ~* A8 u
Extrapolation, 外推法
* K- o, H8 y) [8 Y+ Y! |, _Extreme observation, 末端观测值
( j: F; D' F. v2 `+ OExtremes, 极端值/极值$ d& g- g/ t4 p! F" W
F distribution, F分布
; N6 f+ |% ~" H2 l0 eF test, F检验# X* W6 o1 M1 G _' _
Factor, 因素/因子
2 D3 |/ k% J5 L8 {+ gFactor analysis, 因子分析
; G7 s/ o0 [/ {* V/ @4 |Factor Analysis, 因子分析
8 A$ k7 h3 v; S. Y( KFactor score, 因子得分
) \/ J6 `' N% Q4 [Factorial, 阶乘% D) r7 v% b8 e6 W4 q8 O" `( A7 x
Factorial design, 析因试验设计7 y6 a2 T6 x6 c* }
False negative, 假阴性! f- H0 j1 x* K) s* N) w( g( [
False negative error, 假阴性错误
2 ?1 m! ]1 u" H9 C) S) ?Family of distributions, 分布族+ A: J3 a( R- E$ n7 k; D
Family of estimators, 估计量族( m0 Y# _2 ~. x6 g& }. H9 o3 c5 n0 s
Fanning, 扇面9 l% P: K0 x- N
Fatality rate, 病死率- w W! G. d) v. W& E; F
Field investigation, 现场调查# y$ j1 C6 [7 e9 C$ X; W
Field survey, 现场调查+ v9 L* ^5 b2 O0 _) u! c1 H
Finite population, 有限总体
2 _' v8 w3 C' @$ ]' L3 F7 e( DFinite-sample, 有限样本
' E; ]' M" y2 \2 V/ u6 ~First derivative, 一阶导数) a+ T* e- X4 I' u: ?; W
First principal component, 第一主成分
/ a0 F7 \2 V/ ?First quartile, 第一四分位数
1 `+ W: `- W: f$ NFisher information, 费雪信息量
% [7 o5 d4 N& W6 M* y" W5 ?3 |# V( sFitted value, 拟合值6 }7 o9 X/ b" ]/ a2 U4 d# ]* G
Fitting a curve, 曲线拟合
- Y6 G" S+ f. x' ~; GFixed base, 定基% w+ L! X% ]3 Q6 L: g! W
Fluctuation, 随机起伏
Y" L1 m; a, ]* A) A0 H OForecast, 预测
) l( c( v+ e. F1 O4 E- e, [- |) rFour fold table, 四格表
9 E- e4 q6 {& I: _; Y7 RFourth, 四分点) @) j" P0 X; U+ L1 b
Fraction blow, 左侧比率
% j) c& c$ h" l2 E' k a& |Fractional error, 相对误差
" i3 k: s$ p( j; b* wFrequency, 频率/ x- H, S ]2 h+ O& B* M0 Q
Frequency polygon, 频数多边图
$ E0 t9 }2 A; ?# M. mFrontier point, 界限点
8 s# J5 I9 f% A `Function relationship, 泛函关系 p3 j$ L* K# `' r0 R( o
Gamma distribution, 伽玛分布
6 n8 o/ z0 P+ b5 AGauss increment, 高斯增量& ^ \+ T* i6 G; F/ x. T& W
Gaussian distribution, 高斯分布/正态分布: C# j' a* R- a
Gauss-Newton increment, 高斯-牛顿增量3 e# u: p, G. o2 A3 u9 F- A
General census, 全面普查
4 T# L$ G/ h7 W7 ^5 ]+ _- b( S1 o" |- xGENLOG (Generalized liner models), 广义线性模型
# s+ I8 I3 w) J! O2 F: ?Geometric mean, 几何平均数
5 {5 [2 P( m- Y( h1 B$ K# }* U* i' pGini's mean difference, 基尼均差
) M: ~$ W0 Q. L6 K+ uGLM (General liner models), 一般线性模型
" y- j4 G" i! B3 c$ [/ KGoodness of fit, 拟和优度/配合度
' ]! i. g- i4 W1 X% yGradient of determinant, 行列式的梯度3 |/ b# _ f( \" ]/ x/ z" w2 @
Graeco-Latin square, 希腊拉丁方3 D$ Q/ E, N. y) J1 }1 E
Grand mean, 总均值
, b0 t' |4 i5 L3 @. `Gross errors, 重大错误
. ]) O* I |1 J) rGross-error sensitivity, 大错敏感度" L* X& A; Q/ [5 {. c: v9 _
Group averages, 分组平均3 {- R: `8 _& n- g' t1 }! Z
Grouped data, 分组资料) A& }9 u, j$ s8 I5 S
Guessed mean, 假定平均数
# n& A* F0 Q" M- \0 C; M( L2 |Half-life, 半衰期
: N6 V$ F0 B; @: T* `Hampel M-estimators, 汉佩尔M估计量. e% A" N2 i, C$ F
Happenstance, 偶然事件
, L% _. t% w3 f) z8 I0 ]Harmonic mean, 调和均数
' C6 d D) [/ ]2 l R6 u9 c* kHazard function, 风险均数& s+ Z2 [6 U; c8 L6 h% Y0 N
Hazard rate, 风险率
; O& F/ _: S* j& C2 v' WHeading, 标目
1 f7 D4 v# i; c* y& y4 Q o. S; THeavy-tailed distribution, 重尾分布
5 J4 Y* A( z% Z' y, `! r4 }Hessian array, 海森立体阵
5 ~; z; S( X* {8 _Heterogeneity, 不同质0 t+ y3 R2 y% S+ _% P$ {
Heterogeneity of variance, 方差不齐 9 Y5 l* j# K: a) D) u4 d( b9 ]
Hierarchical classification, 组内分组9 @6 W$ M% j! ?1 _7 D4 i
Hierarchical clustering method, 系统聚类法& F/ H; `8 d% f( s
High-leverage point, 高杠杆率点
! `3 E) U, Y$ z6 |HILOGLINEAR, 多维列联表的层次对数线性模型
) z3 V" @* m" V5 i s6 C8 mHinge, 折叶点! D6 W4 [* j5 C8 d( e+ Y
Histogram, 直方图
8 I/ y: f( T$ y) L3 ?5 K! jHistorical cohort study, 历史性队列研究 2 R8 r& ]8 R: T2 \- _ H3 h
Holes, 空洞
& E, e5 q2 p$ s1 MHOMALS, 多重响应分析
% C- W/ C, y6 `% u+ ~# ]Homogeneity of variance, 方差齐性
# F0 m$ A2 m8 L+ T6 dHomogeneity test, 齐性检验6 V1 l/ {8 P. o. ^/ Z0 O s
Huber M-estimators, 休伯M估计量
. N' H! {7 S, V9 [$ @2 b p+ GHyperbola, 双曲线
% j- o# s- p3 hHypothesis testing, 假设检验9 @: W6 F6 C: l5 z# q
Hypothetical universe, 假设总体+ _2 Z' X3 f4 U$ I9 H
Impossible event, 不可能事件( L6 q% j0 [( e3 M; n
Independence, 独立性
+ [, S* R5 z8 NIndependent variable, 自变量' ~6 s6 t9 \ ]) E0 s
Index, 指标/指数
9 _+ `( ^9 [: ~( bIndirect standardization, 间接标准化法 Q5 N5 O8 F% n! U, l
Individual, 个体 g+ u @' l2 k" k3 }% X. O
Inference band, 推断带
. `' |2 _7 j8 I* w0 pInfinite population, 无限总体
) h9 {6 @! G; p) }( N8 TInfinitely great, 无穷大
* v# A, O# k7 x7 S0 RInfinitely small, 无穷小
3 u) L# r; R8 T6 J7 B dInfluence curve, 影响曲线
7 i% P+ x( N+ W: E$ C( qInformation capacity, 信息容量
$ a4 x, W2 T3 X, JInitial condition, 初始条件% K) S) F6 A O; V* L1 ?
Initial estimate, 初始估计值
' S" W- R j0 F e/ F8 S% QInitial level, 最初水平
0 n- Y% x* o/ U6 g% [1 [Interaction, 交互作用0 G3 r8 d1 r4 X4 g5 C" ^3 C9 ^: z
Interaction terms, 交互作用项" d/ w! `( s2 b" I$ I
Intercept, 截距- Z7 {7 f& z% O' L. f
Interpolation, 内插法; n9 f5 {. k; o4 \ n8 P
Interquartile range, 四分位距1 M6 P' ]1 S( u f
Interval estimation, 区间估计
0 m2 g5 K; w. P" @Intervals of equal probability, 等概率区间2 s) w6 B* H w+ d. b% L* @. W
Intrinsic curvature, 固有曲率' A6 I4 G& a* ^
Invariance, 不变性. A- u: e8 h( G2 d+ h$ M# w: ]; G
Inverse matrix, 逆矩阵
; `6 v1 w# @, @. lInverse probability, 逆概率; y+ W. o* ^- k
Inverse sine transformation, 反正弦变换( ~ u. _6 x. `3 |+ F4 F
Iteration, 迭代
! g& E2 [" y7 o+ U7 c+ f2 \" B/ _Jacobian determinant, 雅可比行列式
/ q' [) I) s: F- C) h" {8 F! yJoint distribution function, 分布函数& J6 L/ F5 A0 l1 S4 j' ]' C9 z2 Y
Joint probability, 联合概率
: E4 N6 l0 { uJoint probability distribution, 联合概率分布" k3 R, X% Y, j: s" q
K means method, 逐步聚类法
4 h. ]) M, r5 E0 y* d( yKaplan-Meier, 评估事件的时间长度
' L$ W* A; I( U0 ^" N- jKaplan-Merier chart, Kaplan-Merier图
$ i, D: Z8 ?: [2 ]$ RKendall's rank correlation, Kendall等级相关
/ h) F, G/ W. x( J" ~Kinetic, 动力学
# E1 B* p" z3 r" D6 p B4 MKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验& q2 a, T. G$ u2 @! j8 W, U( W- V
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验- s$ E+ T6 G4 N) P
Kurtosis, 峰度
1 h' f; U0 L5 D4 @4 p" U5 CLack of fit, 失拟 n& b9 e2 I( p7 R- O9 l4 V
Ladder of powers, 幂阶梯
( M( _/ g1 ^3 lLag, 滞后$ u0 J) i$ o! _! `0 u9 V
Large sample, 大样本
i% J2 i: X) h7 ~' J- eLarge sample test, 大样本检验 @- C4 `- o' O/ U5 Z
Latin square, 拉丁方
4 V' R8 v6 X3 T/ I8 _5 WLatin square design, 拉丁方设计
- F! C4 Y9 H9 y7 a( D& H8 {0 t& ZLeakage, 泄漏+ w! c i/ p; [; q$ s, X8 s
Least favorable configuration, 最不利构形
y; ]. B& _2 u2 n7 i% E; y7 q9 _3 qLeast favorable distribution, 最不利分布
5 D% J$ `0 K7 J# _8 ~7 dLeast significant difference, 最小显著差法4 [' K* L) M5 \3 I1 S9 U+ k% C
Least square method, 最小二乘法
5 p+ m+ O! b8 H" o* F3 ?5 z& ILeast-absolute-residuals estimates, 最小绝对残差估计
; A5 Y4 i2 N. d7 lLeast-absolute-residuals fit, 最小绝对残差拟合. N# u. J: o' M7 P, Y4 P2 l
Least-absolute-residuals line, 最小绝对残差线
! U# H5 E( N. v4 N7 y W! DLegend, 图例
& T8 N" y; j# U5 j: d2 KL-estimator, L估计量
8 S* D7 ^- H( B/ N9 nL-estimator of location, 位置L估计量& H( M1 S1 d( E+ ~' R( O
L-estimator of scale, 尺度L估计量
( f+ g4 w5 Z& v- PLevel, 水平
- b# }, u0 C+ ^. jLife expectance, 预期期望寿命6 m3 z, v' F I7 H# p# e
Life table, 寿命表
( ?' ]5 X8 M6 S+ lLife table method, 生命表法
" H9 o, E* S6 z* s! ~5 dLight-tailed distribution, 轻尾分布
) |2 u- G( i) a( ELikelihood function, 似然函数. W: l" i# u# \& t2 l8 W# P
Likelihood ratio, 似然比* \6 h: G8 v0 B9 ?5 f" n, l
line graph, 线图3 l8 `* M- l8 C$ V
Linear correlation, 直线相关
( f( k$ V7 c: ELinear equation, 线性方程
7 ]2 T# l/ n kLinear programming, 线性规划
; T Q) Z2 T. Q; mLinear regression, 直线回归% s- t7 r. H- [
Linear Regression, 线性回归# C, Z; j9 |. F' Y2 L
Linear trend, 线性趋势
0 J- O, A1 v7 Y lLoading, 载荷 # w6 V$ b. R& n7 }- N
Location and scale equivariance, 位置尺度同变性! R+ J3 s: R w+ @& b2 E9 v
Location equivariance, 位置同变性0 l+ }. x. ?7 L4 G8 x; q2 F
Location invariance, 位置不变性
+ x9 I6 R* W/ B& m SLocation scale family, 位置尺度族
3 M- h! ~6 `: B! ^) D: ?Log rank test, 时序检验 ! n6 o' z( g9 j: F1 S- N- k
Logarithmic curve, 对数曲线
2 m; x/ t* d' m8 b9 @Logarithmic normal distribution, 对数正态分布
e5 @2 v$ \8 Q3 ?. h- k: HLogarithmic scale, 对数尺度- L- d- K" f. \& M: E3 ~
Logarithmic transformation, 对数变换
, F% L, _( I6 O0 ^6 NLogic check, 逻辑检查
% N: O) c E. E7 t$ _) k: mLogistic distribution, 逻辑斯特分布
- |. d6 h. Q. `% X# E0 j, ULogit transformation, Logit转换" b/ o0 c1 ^2 P2 C( I3 R
LOGLINEAR, 多维列联表通用模型
1 Y3 X8 ]3 u+ \9 yLognormal distribution, 对数正态分布9 S& \/ x# U3 T6 e( j
Lost function, 损失函数9 i9 q6 J- W; M" S8 M& [& c
Low correlation, 低度相关8 b$ v; M( M; h* U
Lower limit, 下限- f- P Q1 S2 V- p9 E) I. T
Lowest-attained variance, 最小可达方差
+ P, ^- Y* M$ R9 s* t9 L! @LSD, 最小显著差法的简称7 C9 u7 U+ }, [
Lurking variable, 潜在变量 F9 N* S5 j4 w' ~
Main effect, 主效应
6 `# k/ I$ h2 w+ l" o, nMajor heading, 主辞标目$ b" v9 |5 u6 |/ O! b, }. o4 J0 _
Marginal density function, 边缘密度函数
3 ~* g5 f- E5 d; C0 tMarginal probability, 边缘概率% ]: B, Z [+ U/ S* k* A
Marginal probability distribution, 边缘概率分布+ ~$ v0 _( O( E) M' ]) @4 }9 t2 O
Matched data, 配对资料, O. C2 S& [" P6 \) f- E
Matched distribution, 匹配过分布
! X) M) e4 @8 h* V, CMatching of distribution, 分布的匹配- ]/ k& P! j: l! F K& N
Matching of transformation, 变换的匹配+ \" T: M; G+ m" s, H' X& {7 q- B
Mathematical expectation, 数学期望
1 h6 g5 f* ?( ] R" d7 N0 EMathematical model, 数学模型4 q6 \0 e3 k2 u4 ?& Y* x- i
Maximum L-estimator, 极大极小L 估计量4 ~; e9 ]0 o! k0 n
Maximum likelihood method, 最大似然法
' h. x: H" K7 K, G. l1 s' ]Mean, 均数
4 }2 u- D0 I' }+ k' ]. }" ?Mean squares between groups, 组间均方, c$ z* N' S0 C
Mean squares within group, 组内均方4 S0 Q* d! L+ t* }3 k5 P8 J; \9 Z
Means (Compare means), 均值-均值比较
( m G M, X# u1 v* f. uMedian, 中位数% v8 U# b6 D& K, U m$ b; b( p
Median effective dose, 半数效量+ ^9 R! b, f+ G& n& b' H. w0 C
Median lethal dose, 半数致死量8 q" z( m0 y2 O7 o5 q" o! @' B1 W- k' W. d
Median polish, 中位数平滑' }/ P7 U- G/ }* [/ ?
Median test, 中位数检验
) o6 ?, l" Z: nMinimal sufficient statistic, 最小充分统计量
+ \& B+ u2 K# f* K: ^Minimum distance estimation, 最小距离估计, }! N- b# L0 b% |) i$ U
Minimum effective dose, 最小有效量+ ?; D0 z6 D" i B3 v* o. E z% K
Minimum lethal dose, 最小致死量
' s5 T3 ^8 g+ H' b6 fMinimum variance estimator, 最小方差估计量
. q3 n. E2 ~/ mMINITAB, 统计软件包
: _5 J0 J& [4 ]) n* g0 a1 oMinor heading, 宾词标目
6 s R1 D& U. u4 E* dMissing data, 缺失值7 E. y! ?/ f/ ?( I
Model specification, 模型的确定
, m/ ?' k9 H* ^% o# x/ u- _" KModeling Statistics , 模型统计
+ j3 K% }( ~5 M9 g1 |0 ?Models for outliers, 离群值模型
! _9 ^1 @2 t* S0 z( zModifying the model, 模型的修正 t$ F0 W7 }( Z$ w
Modulus of continuity, 连续性模
$ Z# s2 K/ e% ZMorbidity, 发病率 7 d% W! p d1 ?( P& K/ `5 V9 \( H2 d
Most favorable configuration, 最有利构形
3 [" O: G' J# Z& v9 nMultidimensional Scaling (ASCAL), 多维尺度/多维标度! X% N/ }! z/ X
Multinomial Logistic Regression , 多项逻辑斯蒂回归8 T5 H! a/ t" K1 A% r3 d2 B4 ?! ]
Multiple comparison, 多重比较
& Z: c) t! z4 m/ A6 O# `5 m+ Z) {" \Multiple correlation , 复相关
& ]) K! U8 a4 N2 ~+ hMultiple covariance, 多元协方差
7 K$ ]9 {/ i9 ]" k4 J4 G6 bMultiple linear regression, 多元线性回归: y2 R' Z) s- z8 `
Multiple response , 多重选项
5 p0 n8 h, n6 L+ z+ n; KMultiple solutions, 多解" D$ \$ B w0 ?! N# k0 R9 s2 M
Multiplication theorem, 乘法定理+ e/ \! t+ ^0 Q! w5 r0 f
Multiresponse, 多元响应) `. A7 R8 T" k
Multi-stage sampling, 多阶段抽样' z3 r6 e% P- b! U; G% ]
Multivariate T distribution, 多元T分布
3 e% M' i- n" F& j- q2 GMutual exclusive, 互不相容
" W( ]5 o4 t" @' fMutual independence, 互相独立; ^. ?# V' X, P2 j' l2 \# D& P
Natural boundary, 自然边界* H% d' P/ F+ F1 u8 ?0 C9 E
Natural dead, 自然死亡9 E5 T" R3 d u( H+ ^* r
Natural zero, 自然零
, r- X, Q7 T2 b5 {Negative correlation, 负相关
- \, E8 p9 G/ N1 ]8 l* {Negative linear correlation, 负线性相关; v+ f3 h4 m; V* E2 V) d
Negatively skewed, 负偏" q/ [' Y" v, B- f& k# Y
Newman-Keuls method, q检验
8 A- `+ V0 u; y: ?- u- N7 v2 HNK method, q检验4 p# l/ t- i* W ?& k
No statistical significance, 无统计意义 j. G% L: a4 c) Q, D6 A4 I
Nominal variable, 名义变量. \3 k8 D6 y) U3 a
Nonconstancy of variability, 变异的非定常性
' |. a% R* C* {$ F4 z' S$ bNonlinear regression, 非线性相关
$ \* t1 w+ ^" D: j o& k" A7 x2 jNonparametric statistics, 非参数统计
! g* U4 B# ~' j# PNonparametric test, 非参数检验
2 {# D" l( h6 {9 `- g ~" y1 W6 ?Nonparametric tests, 非参数检验8 @* i& d* c5 [( T1 k9 n
Normal deviate, 正态离差5 d# }, K$ q- K& J9 j
Normal distribution, 正态分布/ @$ V0 A4 P& N4 V, n
Normal equation, 正规方程组
" k7 |; D: |- Q0 N; yNormal ranges, 正常范围
: E8 f) I# |. h6 nNormal value, 正常值
! j3 f4 K; B1 B3 Q' |Nuisance parameter, 多余参数/讨厌参数- f. w) _/ K! W- O, B
Null hypothesis, 无效假设 / z5 L. d% Z( U- b4 \0 c& H1 R
Numerical variable, 数值变量& U# ^9 I' q% ?+ _! u- M! y
Objective function, 目标函数6 J$ x2 s+ x* L! I" t5 I7 ?
Observation unit, 观察单位, s0 q+ ?- j% x' R. R' w& s
Observed value, 观察值4 r; P% p1 d& H% \8 ]
One sided test, 单侧检验5 f3 \! E' T+ P1 E9 b
One-way analysis of variance, 单因素方差分析
9 c' N$ y3 j- [0 z) u# a- k5 zOneway ANOVA , 单因素方差分析8 _2 }0 G7 ]1 M5 N3 M7 h: O4 [
Open sequential trial, 开放型序贯设计; {8 D, }) `( y
Optrim, 优切尾' o, Q' |% F" q8 Q3 ^8 }# ~
Optrim efficiency, 优切尾效率7 H9 g |8 U7 j$ ?9 b1 _+ `2 m( u
Order statistics, 顺序统计量
! |3 [* }) N2 S" B ]6 w0 ^Ordered categories, 有序分类- o) {/ t$ Y: X( Y* e
Ordinal logistic regression , 序数逻辑斯蒂回归
9 I- b: N" X2 s: FOrdinal variable, 有序变量# D0 O4 i5 t' T# `
Orthogonal basis, 正交基5 C p% Z3 G7 ?4 X3 ]( V7 L
Orthogonal design, 正交试验设计5 b" K$ L) E5 A
Orthogonality conditions, 正交条件5 I% V6 a. @: N& P4 [- a
ORTHOPLAN, 正交设计 $ ]; A1 S* Y2 j0 W/ k: t- u5 l! h
Outlier cutoffs, 离群值截断点5 v7 W' V" O* z/ o+ j
Outliers, 极端值/ ?3 u1 L2 B+ T
OVERALS , 多组变量的非线性正规相关 7 t/ D$ s9 a2 e2 z$ z$ Z) H! J
Overshoot, 迭代过度! H }3 G" r a; d
Paired design, 配对设计
; Y# t7 x, S+ u, f5 Z6 uPaired sample, 配对样本: z: x( ?5 ]1 M# u
Pairwise slopes, 成对斜率% Q& ]0 i9 \: g5 h* O3 ^
Parabola, 抛物线
( g; {: d, m+ h. wParallel tests, 平行试验, D( Y. i# a6 q
Parameter, 参数
# Z( }3 z; t# _) Q, dParametric statistics, 参数统计$ c$ m m, q- Z2 w: V
Parametric test, 参数检验7 }4 b( u/ K& h; L/ Y8 g
Partial correlation, 偏相关
1 {: w+ _) ^& a. ]: ePartial regression, 偏回归/ N$ c$ g" n; t7 z6 ^
Partial sorting, 偏排序) T$ L' L7 d3 J: ]" i' D
Partials residuals, 偏残差
/ z- A0 }& j1 ]4 B2 D5 ePattern, 模式
% n. g! A9 U! t! wPearson curves, 皮尔逊曲线
1 s& f9 c# g& A0 Y& oPeeling, 退层
, ~, v2 Z ?3 A+ ZPercent bar graph, 百分条形图
5 z# S9 v4 z9 |1 WPercentage, 百分比
! y$ v' `" B' Y1 o. m( dPercentile, 百分位数1 l/ D; u8 Q& s% `! i6 e2 Y
Percentile curves, 百分位曲线
! @) a7 f0 |( wPeriodicity, 周期性
5 _, p; @6 J3 N+ h8 g i s; D! YPermutation, 排列
3 `! _/ s3 \7 d- r# j- d3 j+ d% xP-estimator, P估计量) l7 {& D; C* H, a( s, U! n
Pie graph, 饼图. K E0 e* N( P7 M2 R
Pitman estimator, 皮特曼估计量
: {$ Q8 V) L! i, ^4 F9 bPivot, 枢轴量9 ^ `% M* B- i9 y
Planar, 平坦
7 D$ M- E$ q1 aPlanar assumption, 平面的假设
/ h3 N0 G$ e. G8 h) o) GPLANCARDS, 生成试验的计划卡
6 u. F) ^; e1 h' x) WPoint estimation, 点估计9 T- z( S. a! Z* S- L# r$ M* u
Poisson distribution, 泊松分布; q k# y6 z' o/ m, u) `) z+ y# D* k
Polishing, 平滑
* h3 z/ W6 K) n& vPolled standard deviation, 合并标准差* }7 t5 [" \! [- @
Polled variance, 合并方差
+ X1 W. P0 g9 k4 J) ^3 U q' K# P' MPolygon, 多边图 c3 Y, f$ ~7 ]7 \7 b
Polynomial, 多项式
$ _ p* ^. \- x9 v7 J6 zPolynomial curve, 多项式曲线0 @) R# p* J6 C# U
Population, 总体
+ {+ C8 k2 @8 z9 O. G5 ]; p2 a! ?Population attributable risk, 人群归因危险度
* |3 B" ^& V* v" VPositive correlation, 正相关' Y$ Z+ N) `- _
Positively skewed, 正偏+ ~: b3 r$ {2 Q. J5 y: y5 g
Posterior distribution, 后验分布1 c& F3 m7 o2 Q) } N
Power of a test, 检验效能
# |& |' z4 o* sPrecision, 精密度# p: p, N' _8 I _
Predicted value, 预测值
9 `" W' c2 B/ r% U' gPreliminary analysis, 预备性分析
; S L/ R0 u6 c5 V5 n8 TPrincipal component analysis, 主成分分析
2 S* D' L6 M+ m" S5 B7 v5 P9 Q. W0 M6 ^Prior distribution, 先验分布
, w& H) x6 ?, U- J* R# a' E! uPrior probability, 先验概率9 d9 K. W8 r. Y* D
Probabilistic model, 概率模型, L6 ~3 `3 R6 V& V% g: b
probability, 概率
, ~9 X# f" R4 P8 h7 h: rProbability density, 概率密度5 p# P) p# q0 E. h/ {9 C# V
Product moment, 乘积矩/协方差
# |* e$ ` Q# oProfile trace, 截面迹图
T$ x$ j/ Q2 ?) f) D) NProportion, 比/构成比# L( z) ]0 o6 I& l. ?( k
Proportion allocation in stratified random sampling, 按比例分层随机抽样
; m4 x( @8 Z7 `Proportionate, 成比例3 c& s. _, N: t
Proportionate sub-class numbers, 成比例次级组含量# j' \7 j }7 f0 K' b
Prospective study, 前瞻性调查2 w( T) W5 } ~
Proximities, 亲近性
% a0 o# N5 \/ ^& _$ D) c$ }Pseudo F test, 近似F检验
* w5 q# N. K8 S6 j. Y7 pPseudo model, 近似模型
5 M) ^) i* n+ Y K. O$ m0 y+ h0 cPseudosigma, 伪标准差
: j: k" O. b, qPurposive sampling, 有目的抽样& j5 G' A7 k+ @3 n9 z3 a
QR decomposition, QR分解
. H9 @- d, b) k, ~0 AQuadratic approximation, 二次近似$ N+ s5 u5 c# o( I! c
Qualitative classification, 属性分类
( u* @6 r& a( X0 V, Y/ P% r8 F. J, FQualitative method, 定性方法
) f* X7 E# J# d$ Y. [$ Q1 ZQuantile-quantile plot, 分位数-分位数图/Q-Q图6 h1 }1 B& Q4 R, h& b- V) u r
Quantitative analysis, 定量分析' J$ J4 U' g8 W1 D& d# k) z
Quartile, 四分位数
9 v' M0 y/ i" ]Quick Cluster, 快速聚类- N% x( Z* A' g: V
Radix sort, 基数排序7 u V5 a5 y) j" s |
Random allocation, 随机化分组) h6 a5 r1 z; o( X _
Random blocks design, 随机区组设计) ?( _0 Y; ^% X; A: p
Random event, 随机事件3 C g- _2 N, N6 D6 n
Randomization, 随机化8 w v, f1 h; C+ B/ Q$ ^
Range, 极差/全距: A: A5 v7 {; |5 O
Rank correlation, 等级相关$ {0 v& e9 [7 I- S' g# N- L
Rank sum test, 秩和检验
3 H1 [, x' f* C" }Rank test, 秩检验" v% t0 `& F# @% I g0 M" m/ f! o
Ranked data, 等级资料
4 c, Y! S6 v; ERate, 比率
6 q0 G# K8 y3 N7 D- Y/ [Ratio, 比例; n- P" Z& ^ E! G6 F! ^
Raw data, 原始资料
" H' `" z9 j, v0 V0 j3 S/ D% gRaw residual, 原始残差5 ~8 \0 l% A+ |% A2 P. }
Rayleigh's test, 雷氏检验
7 e f6 q" L; W7 k2 P* S7 S3 q- mRayleigh's Z, 雷氏Z值
2 t* P2 Z* h% S9 ^Reciprocal, 倒数
- |! G; ]8 z7 f0 P n( T) |Reciprocal transformation, 倒数变换# S& V+ R; B: b: | X: I5 K; P1 U
Recording, 记录" }0 j* D. A/ i+ V; }7 j
Redescending estimators, 回降估计量
$ o U- b6 C# V) l+ `; |Reducing dimensions, 降维
. O% }' u: ` |7 i$ MRe-expression, 重新表达
- ?- b l' O+ N2 hReference set, 标准组0 @& o5 f# |+ L2 e3 v; S" j
Region of acceptance, 接受域" s, c2 j. ]/ e2 }8 S: O" t: n# f
Regression coefficient, 回归系数3 E- C% `& S1 e, @
Regression sum of square, 回归平方和
! d2 K- O; }6 c, LRejection point, 拒绝点
' l5 Z# _0 g. t7 jRelative dispersion, 相对离散度
9 r' W$ p8 C9 f( `$ GRelative number, 相对数
* z% i& t- b* V+ {$ B3 \( dReliability, 可靠性/ g) G" p Z2 e: }3 j
Reparametrization, 重新设置参数
' n: n) ]! L( x% d gReplication, 重复' c" G, P3 R& ?
Report Summaries, 报告摘要
# @# i5 g: Z1 |1 s. Y. \Residual sum of square, 剩余平方和
1 B: }/ O( m5 i7 \. y" E# x# f& oResistance, 耐抗性, b2 {% A' R7 Z% i4 M2 M% W/ ~
Resistant line, 耐抗线
5 i! U2 f- [2 M( r1 j r$ a. M, AResistant technique, 耐抗技术
. n' ?- u* U; q, t( w% a# QR-estimator of location, 位置R估计量: v' d9 s8 W* S) W; W$ Z" \) L( R& Q
R-estimator of scale, 尺度R估计量
& z2 l2 b. o. M: iRetrospective study, 回顾性调查; H/ `$ D& H1 ~( |4 o+ o% [! S
Ridge trace, 岭迹 l1 l. t) `0 F4 ~
Ridit analysis, Ridit分析* m, l' h6 ]! s" K- d7 q" s* q7 @* A
Rotation, 旋转! g6 O! s. i8 ^, h
Rounding, 舍入
. @0 s4 h& u4 L/ N. I+ L; o" P9 V& ?Row, 行
2 X6 h$ l1 L5 u& WRow effects, 行效应
+ X5 @5 L, Q& K9 V) F. W1 U4 T. X5 V( kRow factor, 行因素6 I8 C1 w& v9 K2 j8 o* u
RXC table, RXC表
3 u$ g( l4 Z/ y+ }; Y8 }' V2 D" CSample, 样本* t7 V+ b) i2 S/ k
Sample regression coefficient, 样本回归系数
7 B) ]" E$ q8 o. v0 `0 ?# RSample size, 样本量, J' y$ S6 |) a
Sample standard deviation, 样本标准差
' V1 [4 H a2 C% Y) HSampling error, 抽样误差5 J2 w3 w3 j: \8 T5 S' J% S( ?% Q
SAS(Statistical analysis system ), SAS统计软件包4 {7 K3 G4 s6 T
Scale, 尺度/量表
: q5 [4 g, K% p9 n1 n/ JScatter diagram, 散点图
5 p e$ l! g8 }! P5 O2 {Schematic plot, 示意图/简图' P' k$ u* n, `( V: q# v. T
Score test, 计分检验7 R6 `0 }+ y) y0 V7 I
Screening, 筛检7 _& N. y( N* F0 @% c0 k
SEASON, 季节分析 6 L8 J9 a+ o1 r$ v% i
Second derivative, 二阶导数) @) ]" o/ ]+ I* V
Second principal component, 第二主成分
$ d- T: U7 r6 o5 @# z* R& g* R' RSEM (Structural equation modeling), 结构化方程模型
3 U4 i, V9 M8 g) i6 T q& `+ gSemi-logarithmic graph, 半对数图
0 V, W1 P7 s8 F+ ISemi-logarithmic paper, 半对数格纸, {) _& L; x0 G @2 r) U+ g
Sensitivity curve, 敏感度曲线' R j H" w1 c# M
Sequential analysis, 贯序分析
9 W+ ?; F. a4 \$ T- {7 BSequential data set, 顺序数据集0 p( m# G+ w, }7 u+ |1 E* ]
Sequential design, 贯序设计$ c& C. E9 H4 m! d- E6 N j
Sequential method, 贯序法: f3 h( }& J/ R" d9 g/ |4 _4 i
Sequential test, 贯序检验法
- ^5 b7 h# b/ p1 [( c# A# [3 j+ h. qSerial tests, 系列试验/ [# a+ `' s1 I: G
Short-cut method, 简捷法 / ?4 I% n: c% P1 `( Q; j
Sigmoid curve, S形曲线
" H) |( V0 i% y, {- i& Y. f! qSign function, 正负号函数
, J3 I. f I9 p) l$ R, y" wSign test, 符号检验/ r5 H1 X$ X- K0 Q: g2 j2 n
Signed rank, 符号秩! J1 d3 S7 U6 V, E- i$ B6 K6 L
Significance test, 显著性检验
- W( ^+ l5 K- I2 I; F2 I+ zSignificant figure, 有效数字
' ]; e4 {8 f" w& }7 p GSimple cluster sampling, 简单整群抽样
$ l& I; i0 U( o4 l4 C7 F+ dSimple correlation, 简单相关% e$ f5 m% A, K$ @5 ?- h
Simple random sampling, 简单随机抽样
8 b* `2 H( \$ b" _; ~Simple regression, 简单回归" i: v% |7 W e' r! i$ ~
simple table, 简单表+ Y9 W- w5 y2 q; Q" F# w2 \0 b
Sine estimator, 正弦估计量
8 o3 M7 L9 g5 t9 z0 }Single-valued estimate, 单值估计
! u& ^9 T% C/ P0 iSingular matrix, 奇异矩阵) A% t: ^1 B3 P6 \" B
Skewed distribution, 偏斜分布
& X: N! p) I' J1 m! g" M, t" l9 OSkewness, 偏度
( D0 e4 ]! y4 @Slash distribution, 斜线分布1 o* m" F6 T) H# Q
Slope, 斜率2 \0 K F: o% } X, V( o$ j9 ]
Smirnov test, 斯米尔诺夫检验9 X h' D' ?6 T% S& c
Source of variation, 变异来源
$ W k; h4 X' u' rSpearman rank correlation, 斯皮尔曼等级相关
, c5 j) a5 T# M/ ?/ K. B* N) |) `. G7 MSpecific factor, 特殊因子
' y+ \9 Z* q+ m0 G: l" Q, hSpecific factor variance, 特殊因子方差+ P( b5 G* `) M2 R* F
Spectra , 频谱0 e2 S9 V/ j- e. g9 d' n
Spherical distribution, 球型正态分布3 D& a" Z# e3 t7 e
Spread, 展布
" ~1 j* a4 f. }: oSPSS(Statistical package for the social science), SPSS统计软件包9 l. U( a" u2 i% }. X! N9 C" m
Spurious correlation, 假性相关
" z4 A7 U6 s+ hSquare root transformation, 平方根变换, C! ^/ P# R2 g; o5 T. a
Stabilizing variance, 稳定方差
" y5 T" I3 Y6 T) K0 \! f% wStandard deviation, 标准差
! e$ k# z& g3 X% ?$ n8 H7 hStandard error, 标准误
7 i: w9 |- x' LStandard error of difference, 差别的标准误
; }, K, H! P b& U eStandard error of estimate, 标准估计误差! E/ a7 E9 e" E/ h
Standard error of rate, 率的标准误/ w0 t" y9 a% X2 W" h ^1 f' s$ K$ e
Standard normal distribution, 标准正态分布
- y2 ~! P4 x/ y) FStandardization, 标准化
M' l6 R/ i/ H! P/ \% gStarting value, 起始值' u, S5 H5 O* c7 M. i- d: f) O4 G
Statistic, 统计量
7 R9 u1 s+ X0 C& {Statistical control, 统计控制! S, v/ S7 {2 B# c! m# U4 u/ h: m( G
Statistical graph, 统计图
% {, F" c8 f% J6 N! D7 m ]$ UStatistical inference, 统计推断
' J- @0 v! r/ a7 ^& F# H( IStatistical table, 统计表' @" T) n# o: w' q" z( \
Steepest descent, 最速下降法
' M5 d( E+ y7 f; p) c2 ~Stem and leaf display, 茎叶图
$ U( }* n2 r. JStep factor, 步长因子
! _0 ^7 w% \7 y" \& V; eStepwise regression, 逐步回归
]' G8 U/ V+ P% y* p" dStorage, 存' F+ C# ^- A3 @: p- }3 D
Strata, 层（复数）1 Q8 n. w, Q- n+ J8 q) A$ ]
Stratified sampling, 分层抽样
2 k6 L, P$ N0 S- fStratified sampling, 分层抽样& R2 u) e0 s5 [) Y
Strength, 强度8 O4 j( O: }2 F7 @$ F. N
Stringency, 严密性
/ [! F! x8 P3 a0 |8 R# W: d1 hStructural relationship, 结构关系5 y' H9 y$ Z h$ j' C
Studentized residual, 学生化残差/t化残差" T2 b! N2 O# e" b$ A1 s( M; p4 C9 E
Sub-class numbers, 次级组含量
1 j0 l* [, T, H/ \5 J+ [: C4 u9 fSubdividing, 分割( h# a& }7 e3 A7 ~3 n
Sufficient statistic, 充分统计量; j4 v- s. d$ B/ S
Sum of products, 积和; d1 c% g+ X# K$ e) Z
Sum of squares, 离差平方和, R+ ~) c4 `5 B/ l
Sum of squares about regression, 回归平方和& W _4 A% z, t* r* ~
Sum of squares between groups, 组间平方和1 w( f" R. G& n# T j, ?* |; A
Sum of squares of partial regression, 偏回归平方和
! C3 P) q& C% d- W' d. H2 |& r+ x1 G0 RSure event, 必然事件! h: F7 @& G; r' P
Survey, 调查# [$ |( i I6 H \- d$ O
Survival, 生存分析, u5 B2 `$ P4 s% n8 {& g- l! v
Survival rate, 生存率
: P( K! M0 @- i. w$ r, A. lSuspended root gram, 悬吊根图
1 d1 p& I% T6 F: W- Y& t. }Symmetry, 对称* j3 N$ x) s9 {7 B- _( v" ~8 T
Systematic error, 系统误差
- c G( J3 B+ x8 J1 ^Systematic sampling, 系统抽样/ M7 d7 \! Y7 t2 B$ n/ n
Tags, 标签1 M5 {; k3 R: o; k7 u8 s" U* i2 t) f
Tail area, 尾部面积
- |) f) D4 s& b4 B: mTail length, 尾长( i! l$ t. n2 u) `; U7 ^3 W
Tail weight, 尾重* [8 j8 y9 X& s& f0 j
Tangent line, 切线( F- {3 W( q: ^, o0 Q* C
Target distribution, 目标分布
4 F @! Y6 N5 N3 H; Q4 hTaylor series, 泰勒级数
9 q8 t! m' A7 ?9 WTendency of dispersion, 离散趋势8 ]8 `: x% w+ a( p! Z# J
Testing of hypotheses, 假设检验
! f3 q% v! ? H. V) d( }) gTheoretical frequency, 理论频数+ K, N1 \9 `$ d2 ]" z g5 N- S3 q
Time series, 时间序列
3 W/ }( o8 v, ]5 ]: iTolerance interval, 容忍区间
- `' B1 _) o5 \% W3 h6 lTolerance lower limit, 容忍下限. j' \1 i+ F+ N3 s: E1 d5 g
Tolerance upper limit, 容忍上限 W) p) I( x+ t
Torsion, 扰率
" U4 r8 Z6 n- m, R& ~/ k2 [3 STotal sum of square, 总平方和6 i. ~ M& e8 F5 I0 s% P. r
Total variation, 总变异
: h" K$ g; A" w3 Q, R5 UTransformation, 转换
1 B+ H; p/ V! Q6 GTreatment, 处理6 `$ g. D; E0 ? A
Trend, 趋势2 c5 i4 b& i1 ^. B8 Q1 d* q2 ]3 a
Trend of percentage, 百分比趋势
% G" w/ @1 r2 C, g& T* N! STrial, 试验
! K$ r& x( M! E* \# ~Trial and error method, 试错法
6 i' Y1 R4 N) e! y- D; kTuning constant, 细调常数! J* V# X4 b& |4 r/ n. V0 d& u
Two sided test, 双向检验: D5 l4 b- ?, d# C; n
Two-stage least squares, 二阶最小平方+ n: q9 I9 I. _- {+ y$ [- a
Two-stage sampling, 二阶段抽样
, D" h2 q& i/ ^Two-tailed test, 双侧检验5 l/ ?- P2 b6 Z- P
Two-way analysis of variance, 双因素方差分析
+ i3 c6 n" u7 g W8 z: W, RTwo-way table, 双向表
2 J5 ^) G- H2 j/ `Type I error, 一类错误/α错误' N) L* ^$ o; F) E5 ^4 [
Type II error, 二类错误/β错误
( U. q; E2 j1 K6 qUMVU, 方差一致最小无偏估计简称& w5 U: Q0 O( l6 ^% ~/ `# L
Unbiased estimate, 无偏估计9 i3 ~+ R ~ h5 Z: P$ Z
Unconstrained nonlinear regression , 无约束非线性回归
8 Z, l# C, |, MUnequal subclass number, 不等次级组含量, W5 u) C, j9 A5 j, ~4 j
Ungrouped data, 不分组资料
5 o$ V3 r$ C. sUniform coordinate, 均匀坐标
- {9 l2 ?; _) k: {1 k* kUniform distribution, 均匀分布
' }( q$ r& g- a' o& [4 ]4 l! fUniformly minimum variance unbiased estimate, 方差一致最小无偏估计) K" M* b1 x- C4 }) T
Unit, 单元+ k* }8 _" [4 ^( A1 {2 L ]
Unordered categories, 无序分类! B/ f3 E, i# ?7 e4 O
Upper limit, 上限
2 b7 J7 ]0 @' j' |; yUpward rank, 升秩
# E7 @5 o/ _$ PVague concept, 模糊概念
# i9 C! D% N6 ?+ k& IValidity, 有效性$ k- J( N% P/ F" Q8 `+ Y
VARCOMP (Variance component estimation), 方差元素估计
& ^: \" L+ p% W) d( T5 i" |Variability, 变异性
5 `) D" K$ h9 K+ g: w( z& X: }Variable, 变量
( W8 _3 b3 U; p% X7 M# cVariance, 方差
# j2 B) b0 S9 sVariation, 变异% s. c4 j) v* C' Q) e4 Q
Varimax orthogonal rotation, 方差最大正交旋转
1 a% \; h* l, h0 u8 hVolume of distribution, 容积
4 |% c. X; Y- v% } a7 G( l+ h7 AW test, W检验
; }, o- a/ Y2 J( i( n" FWeibull distribution, 威布尔分布
3 g, T0 |' ^; G+ z: tWeight, 权数
* X& v5 P h7 W+ ^# oWeighted Chi-square test, 加权卡方检验/Cochran检验6 R7 `. O$ |: `7 N+ T% k
Weighted linear regression method, 加权直线回归# s3 X5 J: Q- W+ d
Weighted mean, 加权平均数! t, x9 H8 s; j0 e8 N
Weighted mean square, 加权平均方差
0 C, s8 v& w8 {3 DWeighted sum of square, 加权平方和 p+ T* S2 o. k9 X3 R* p
Weighting coefficient, 权重系数
1 y' K1 e5 D( @( p( q& kWeighting method, 加权法 9 h4 ]9 ]4 b" N& A" n; x) z; f
W-estimation, W估计量/ t4 v6 z, I4 J& U: E+ W
W-estimation of location, 位置W估计量
6 @3 z! ]% g) x# QWidth, 宽度
. u* D5 q! y) R, vWilcoxon paired test, 威斯康星配对法/配对符号秩和检验1 ]0 w9 y" E6 P% s
Wild point, 野点/狂点* V5 }* e/ B% Z( y: h5 l
Wild value, 野值/狂值
! Z( w6 p* K1 s. Q5 x) G. _% IWinsorized mean, 缩尾均值
/ m# t% P* O9 z2 vWithdraw, 失访 r5 W/ H* V$ n& ?9 o/ `
Youden's index, 尤登指数
, J1 a5 J' p$ S6 K9 \ I4 xZ test, Z检验5 k% B: ~0 X5 a/ ?
Zero correlation, 零相关
/ o7 f" y) I9 [' WZ-transformation, Z变换 |
本帖子中包含更多资源
您需要 登录 才可以下载或查看，没有账号？注册会员
x
|
|清流社工网
( 苏ICP备19044186号-1 )
发表于 2009-1-6 22:05
